> ## Documentation Index
> Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# LM Studio Embeddings

> Generate embeddings using locally-hosted LM Studio

## Overview

LM Studio provides a user-friendly interface for running embedding models locally.

## Quick Start

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import embedding

result = embedding(
    input="Hello world",
    model="lm_studio/nomic-embed-text",
    api_base="http://localhost:1234/v1"
)
print(f"Dimensions: {len(result.embeddings[0])}")
```

## CLI Usage

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
praisonai embed "Hello world" --model lm_studio/nomic-embed-text
```

## Setup

1. Download and install LM Studio from [https://lmstudio.ai](https://lmstudio.ai)
2. Load an embedding model
3. Start the local server

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
export LM_STUDIO_API_BASE="http://localhost:1234/v1"
```

## Related

* [Embedding Providers Overview](/docs/embeddings/index)
* [Ollama Embeddings](/docs/embeddings/providers/ollama)